Support Vector Machines Applied to Face Recognition

机译：支持向量机在人脸识别中的应用

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Face recognition is a K class problem, where K is the number of known211u001eindividuals; and support vector machines (SVMs) are a binary classification 211u001emethod, By reformulating the face recognition problem and re-interpreting the 211u001eoutput of the SVM classifier, the authors developed a SVM-based face recognition 211u001ealgorithm. The face recognition problem is formulated as a problem in difference 211u001espace, which models dissimilartities between faces of the same person, and 211u001edissimilarities between faces of different people. By modifying the 211u001einterpretation of the decision surface generated by SVM, the authors generated a 211u001esimilarity metric between faces that is learned from examples of differences 211u001ebetween faces. The SVM-based algorithm is compared with a principal component 211u001eanalysis (PCA) based algorithm on a difficult set of images from the FERET 211u001edatabase. Performance was measured for both verification and identification 211u001escenarios.

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Phillips, P. J.;
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年度 1998
页码 1-12
总页数 12
原文格式 PDF
正文语种 eng
中图分类工业技术;
关键词
Face(Anatomy); Pattern recognition; Feature extraction; Vector211 processing(Computers); Identification systems; Image processing; Computer vision; 211 Image analysis; Principal component analysis; Verification; Algorithms;

机译：面部（解剖）;模式识别;特征提取; Vector211处理（计算机）;识别系统;图像处理;计算机视觉; 211图像分析;主成分分析;验证;算法;

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7. Support Vector Machines Applied to Face Recognition [O] . P. Jonathon Phillips 1999

机译：支持向量机在人脸识别中的应用

Support Vector Machines Applied to Face Recognition

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